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27 lines
1.1 KiB
27 lines
1.1 KiB
# Copyright 2020 Huawei Technologies Co., Ltd
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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# ============================================================================
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"""
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Quantization.
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User can use quantization aware to train a model. MindSpore supports quantization aware training,
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which models quantization errors in both the forward and backward passes using fake-quantization
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operations. Note that the entire computation is carried out in floating point. At the end of quantization
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aware training, MindSpore provides conversion functions to convert the trained model into lower precision.
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"""
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from .quant import convert_quant_network
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__all__ = ["convert_quant_network"]
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